ii EPIDEMIOLOGIC TRENDS IN DRUG ABUSE—Foreword
Bibliographic record
Abstract
Community Epidemiology Work Group (CEWG) who have voluntarily invested their time and resources in preparing the reports presented at the meetings. This publication was prepared by MasiMax Resources, Inc., under contract number N01-DA-1-5514 from NIDA. This publication, Epidemiologic Trends in Drug Abuse, Volume II, contains the papers presented and data reported at the June 2003 CEWG meeting by CEWG representatives from 21 areas, and researchers from Canada and Mexico. Volume II also contains a number of special presentations, including a panel on methadone-associated mortality, methamphetamine abuse in Missouri, and updates on the Arrestee Drug Abuse Monitoring (ADAM) program and the National Forensic Laboratory Information System (NFLIS). All material in this volume is in the public domain and may be reproduced or copied without permission from the Institute or the authors. Citation of the source is appreciated. The U.S. Government does not endorse or favor any specific commercial product. Trade or proprietary names appearing in this publication are used only because they are considered essential in the context of the studies reported herein. For more information about the Community Epidemiology Work Group and other researched-based publications and information on drug abuse and addiction, visit NIDA’s
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".